Abstract
Store-based retailers face the challenge of meeting increased customer demands and compete with online marketplaces. big data (BD) can support store-based retail and engage customers locally. We are therefore conducted a three-year mixed-method-study to identify relevant factors for the German store-based retail in three successive phases. Firstly, we qualitatively identify effectiveness-factors using BD through 13 semi-structured-interviews. Secondly, we quantitatively evaluate the relevance of the identified effectiveness-factors (i.a., over 2.8 million data points) using the 7P-Marketing-Mix, and thirdly analyzed significant factors. Our findings show that many store-based retailers lack knowledge about smart town and BD-use, e.g., by creating a network or running joint retail campaigns to increase the towns attractiveness. We provide an overview and guidance on how BD-analysis can effectively influence the store-based retail transformation in smart towns. Using a mixed-method-study in a German towns, we were able to identify which factors influence store-based retail in a smart town and suggest promising interventions.
Recommended Citation
Kreuels, Cindy; Stelter, Aida; Kordyaka, Bastian; and Niehaves, Björn, "Supporting the Store-based Retail with Big Data in German Towns – a Longitudinal Mixed-Method-Study" (2024). Wirtschaftsinformatik 2024 Proceedings. 75.
https://aisel.aisnet.org/wi2024/75